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Development of automatized new indices for radiological assessment of chest-wall deformity and its quantitative evaluation.

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Title: Development of automatized new indices for radiological assessment of chest-wall deformity and its quantitative evaluation.
Authors: Kim, H. C.1,2, Park, H. J.3, Ham, S. Y.4, Nam, K. W.2, Choi, S. Y.5, Oh, J. S.6, Choi, H.7,8, Jeong, G. S.1,2, Park, S. W.9, Kim, M. G.6 mgkim@korea.ac.kr, Sun, K.1,2,3 ksunmd@kumc.or.kr
Source: Medical & Biological Engineering & Computing. Aug2008, Vol. 46 Issue 8, p815-823. 9p. 1 Color Photograph, 3 Diagrams, 2 Charts, 2 Graphs.
Subjects: Chest disease diagnosis, Chest abnormalities, Thoracic surgery, Image processing, Medical imaging systems
Abstract: Pre-operative diagnosis of chest-wall deformity is important for successful surgical correction and post-operative evaluation of funnel chest patients. However, conventional indices that define the severity of deformity have several limitations; manually calculated and cannot supply information about asymmetry. We developed four indices that can represent both the depression and the asymmetry of the chest-wall, and can automatically be extracted by computerized image processing technique. Three indices, including eccentricity index (EI), flatness index (FI), and circularity index (CI), were suggested to represent the depression of the chest-wall, and one index, rotation index (RI), to represent the asymmetry of the chest-wall. To verify the feasibility of new indices, several synthetic images and real CT images were used to analyze the performance of new indices and the statistical relationship with conventional Haller index. The experimental results showed possible application of suggested indices to the diagnosis of funnel chest patient. Suggested indices showed clear trends of change with the severity of chest-wall deformation in regards to both the depression and the asymmetry. Results of statistical analysis showed high correlation between new indices and HI, showing possibility of replacing HI. [ABSTRACT FROM AUTHOR]
Copyright of Medical & Biological Engineering & Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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  Data: <searchLink fieldCode="AR" term="%22Kim%2C+H%2E+C%2E%22">Kim, H. C.</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Park%2C+H%2E+J%2E%22">Park, H. J.</searchLink><relatesTo>3</relatesTo><br /><searchLink fieldCode="AR" term="%22Ham%2C+S%2E+Y%2E%22">Ham, S. Y.</searchLink><relatesTo>4</relatesTo><br /><searchLink fieldCode="AR" term="%22Nam%2C+K%2E+W%2E%22">Nam, K. W.</searchLink><relatesTo>2</relatesTo><br /><searchLink fieldCode="AR" term="%22Choi%2C+S%2E+Y%2E%22">Choi, S. Y.</searchLink><relatesTo>5</relatesTo><br /><searchLink fieldCode="AR" term="%22Oh%2C+J%2E+S%2E%22">Oh, J. S.</searchLink><relatesTo>6</relatesTo><br /><searchLink fieldCode="AR" term="%22Choi%2C+H%2E%22">Choi, H.</searchLink><relatesTo>7,8</relatesTo><br /><searchLink fieldCode="AR" term="%22Jeong%2C+G%2E+S%2E%22">Jeong, G. S.</searchLink><relatesTo>1,2</relatesTo><br /><searchLink fieldCode="AR" term="%22Park%2C+S%2E+W%2E%22">Park, S. W.</searchLink><relatesTo>9</relatesTo><br /><searchLink fieldCode="AR" term="%22Kim%2C+M%2E+G%2E%22">Kim, M. G.</searchLink><relatesTo>6</relatesTo><i> mgkim@korea.ac.kr</i><br /><searchLink fieldCode="AR" term="%22Sun%2C+K%2E%22">Sun, K.</searchLink><relatesTo>1,2,3</relatesTo><i> ksunmd@kumc.or.kr</i>
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  Data: <searchLink fieldCode="JN" term="%22Medical+%26+Biological+Engineering+%26+Computing%22">Medical & Biological Engineering & Computing</searchLink>. Aug2008, Vol. 46 Issue 8, p815-823. 9p. 1 Color Photograph, 3 Diagrams, 2 Charts, 2 Graphs.
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  Data: <searchLink fieldCode="DE" term="%22Chest+disease+diagnosis%22">Chest disease diagnosis</searchLink><br /><searchLink fieldCode="DE" term="%22Chest+abnormalities%22">Chest abnormalities</searchLink><br /><searchLink fieldCode="DE" term="%22Thoracic+surgery%22">Thoracic surgery</searchLink><br /><searchLink fieldCode="DE" term="%22Image+processing%22">Image processing</searchLink><br /><searchLink fieldCode="DE" term="%22Medical+imaging+systems%22">Medical imaging systems</searchLink>
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  Data: Pre-operative diagnosis of chest-wall deformity is important for successful surgical correction and post-operative evaluation of funnel chest patients. However, conventional indices that define the severity of deformity have several limitations; manually calculated and cannot supply information about asymmetry. We developed four indices that can represent both the depression and the asymmetry of the chest-wall, and can automatically be extracted by computerized image processing technique. Three indices, including eccentricity index (EI), flatness index (FI), and circularity index (CI), were suggested to represent the depression of the chest-wall, and one index, rotation index (RI), to represent the asymmetry of the chest-wall. To verify the feasibility of new indices, several synthetic images and real CT images were used to analyze the performance of new indices and the statistical relationship with conventional Haller index. The experimental results showed possible application of suggested indices to the diagnosis of funnel chest patient. Suggested indices showed clear trends of change with the severity of chest-wall deformation in regards to both the depression and the asymmetry. Results of statistical analysis showed high correlation between new indices and HI, showing possibility of replacing HI. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Medical & Biological Engineering & Computing is the property of Springer Nature and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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